Evolutionary Algorithms for Path Coverage Test Data Generation and Optimization: A Review-Reference-Cited by-同舟云学术

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Evolutionary Algorithms for Path Coverage Test Data Generation and Optimization: A Review

Published:2022 Issue: Volume: Page:91-103
ISSN:2522-8595
Container-title:Optimization of Automated Software Testing Using Meta-Heuristic Techniques
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Author:

Rath Dharashree,Parida Swarnalipsa,Mishra Deepti Bala,Pradhan Sonali

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-07297-0_7

Reference38 articles.

1. Chauhan, N. (2010). Software testing: Principles and practices. Oxford University Press.

2. Mall, R. (2018). Fundamentals of software engineering. PHI Learning Pvt. Ltd.

3. Zhu, Z., Xu, X., & Jiao, L. (2017, June). Improved evolutionary generation of test data for multiple paths in search-based software testing. In 2017 IEEE Congress on Evolutionary Computation (CEC) (pp. 612–620). IEEE.

4. Srivastava, P. R., & Kim, T. H. (2009). Application of genetic algorithm in software testing. International Journal of Software Engineering and its Applications, 3(4), 87–96.

5. Alshraideh, M., Mahafzah, B. A., & Al-Sharaeh, S. (2011). A multiple-population genetic algorithm for branch coverage test data generation. Software Quality Journal, 19(3), 489–513.

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